DocumentCode :
1747381
Title :
Ligand binding with OBPRM and user input
Author :
Bayazit, O. Burchan ; Song, Guang ; Amato, Nancy M.
Author_Institution :
Dept. of Comput. Sci., Texas A&M Univ., College Station, TX, USA
Volume :
1
fYear :
2001
fDate :
2001
Firstpage :
954
Abstract :
We present a framework for studying ligand binding which is based on techniques recently developed in the robotics motion planning community. We are interested in locating binding sites on the protein for ligand molecule. Our work investigates the performance of a fully automated motion planner, as well as the effects of supplementary user input collected using a haptic device. Our results applying an obstacle-based probabilistic roadmap motion planning algorithm (OBPRM) to some protein-ligand complexes are encouraging. The framework successfully identified potential building sites for all complexes studied. We find that user input helps the planner, and haptic device helps the user to understand the protein structure by enabling them to feel the difficult-to-visualize forces.
Keywords :
biology computing; bonds (chemical); haptic interfaces; molecular biophysics; path planning; haptic device; ligand binding; motion planning; probabilistic roadmap; protein; Computer science; Drugs; Electrostatic measurements; Haptic interfaces; Motion planning; Position measurement; Potential energy; Proteins; Robotics and automation; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on
ISSN :
1050-4729
Print_ISBN :
0-7803-6576-3
Type :
conf
DOI :
10.1109/ROBOT.2001.932673
Filename :
932673
Link To Document :
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